Key result
This Matters Arising letter requests clarification on the clinical utility, decision curve thresholds, and external calibration of a multitask gradient boosting model for predicting postoperative complications.
This commentary highlights the need for clearer clinical decision contexts, absolute impact metrics for rare outcomes, and detailed calibration reporting to improve the real-world applicability of perioperative prediction models.
This Matters Arising comments on Yoon et al.’s multitask gradient boosting model for predicting acute kidney injury, postoperative respiratory failure and in-hospital mortality after non-cardiac surgery. We ask for clarification on the clinical decision context and threshold ranges in the decision curve analyses, the absolute impact of the model for rare outcomes, and calibration and potential recalibration in external cohorts to support implementation.
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Wo et al. (2026) conducted a letter in Postoperative complications after non-cardiac surgery. Multitask gradient boosting machine (MT-GBM) vs. American Society of Anesthesiologists (ASA) classification was evaluated. This Matters Arising letter requests clarification on the clinical utility, decision curve thresholds, and external calibration of a multitask gradient boosting model for predicting postoperative complications.
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